{
    "description": "Deep research system that conducts multi-turn agent conversations to perform web search, synthesize insights and generate well-structured white papers",
    "usecases": ["Deep Research"],
    "nodes": [
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                "name": "startAgentflow",
                "type": "Start",
                "color": "#7EE787",
                "hideInput": true,
                "baseClasses": ["Start"],
                "category": "Agent Flows",
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                        "label": "Input Type",
                        "name": "startInputType",
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                                "label": "Chat Input",
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                                "description": "Start the conversation with chat input"
                            },
                            {
                                "label": "Form Input",
                                "name": "formInput",
                                "description": "Start the workflow with form inputs"
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                    {
                        "label": "Form Title",
                        "name": "formTitle",
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                        "label": "Form Description",
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                        "placeholder": "Complete all fields below to continue",
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                    {
                        "label": "Form Input Types",
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                                "label": "Label",
                                "name": "label",
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                            {
                                "label": "Variable Name",
                                "name": "name",
                                "type": "string",
                                "placeholder": "Variable name for the input (must be camel case)",
                                "description": "Variable name must be camel case. For example: firstName, lastName, etc."
                            },
                            {
                                "label": "Add Options",
                                "name": "addOptions",
                                "type": "array",
                                "show": {
                                    "formInputTypes[$index].type": "options"
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                                "array": [
                                    {
                                        "label": "Option",
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                        "id": "startAgentflow_0-input-formInputTypes-array",
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                        "label": "Ephemeral Memory",
                        "name": "startEphemeralMemory",
                        "type": "boolean",
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                        "optional": true,
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                        "display": true
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                    {
                        "label": "Flow State",
                        "name": "startState",
                        "description": "Runtime state during the execution of the workflow",
                        "type": "array",
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                            {
                                "label": "Key",
                                "name": "key",
                                "type": "string",
                                "placeholder": "Foo"
                            },
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                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "placeholder": "Bar",
                                "optional": true
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                        "display": true
                    },
                    {
                        "label": "Persist State",
                        "name": "startPersistState",
                        "type": "boolean",
                        "description": "Persist the state in the same session",
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                        "id": "startAgentflow_0-input-startPersistState-boolean",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "startInputType": "chatInput",
                    "startEphemeralMemory": true,
                    "startState": ""
                },
                "outputAnchors": [
                    {
                        "id": "startAgentflow_0-output-startAgentflow",
                        "label": "Start",
                        "name": "startAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "width": 103,
            "height": 66,
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            "positionAbsolute": {
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            "dragging": false
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            "id": "llmAgentflow_0",
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                "id": "llmAgentflow_0",
                "label": "Topic Enhancer",
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                "name": "llmAgentflow",
                "type": "LLM",
                "color": "#64B5F6",
                "baseClasses": ["LLM"],
                "category": "Agent Flows",
                "description": "Large language models to analyze user-provided inputs and generate responses",
                "inputParams": [
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                        "label": "Model",
                        "name": "llmModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "llmAgentflow_0-input-llmModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Messages",
                        "name": "llmMessages",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
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                                "label": "Role",
                                "name": "role",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "System",
                                        "name": "system"
                                    },
                                    {
                                        "label": "Assistant",
                                        "name": "assistant"
                                    },
                                    {
                                        "label": "Developer",
                                        "name": "developer"
                                    },
                                    {
                                        "label": "User",
                                        "name": "user"
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                                ]
                            },
                            {
                                "label": "Content",
                                "name": "content",
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                                "generateInstruction": true,
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                        "label": "Enable Memory",
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                        "label": "Memory Type",
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                                "label": "All Messages",
                                "name": "allMessages",
                                "description": "Retrieve all messages from the conversation"
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                                "description": "Uses a fixed window size to surface the last N messages"
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                                "label": "Conversation Summary",
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                            },
                            {
                                "label": "Conversation Summary Buffer",
                                "name": "conversationSummaryBuffer",
                                "description": "Summarize conversations once token limit is reached. Default to 2000"
                            }
                        ],
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                        "default": "allMessages",
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                            "llmEnableMemory": true
                        },
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                        "type": "number",
                        "default": "20",
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                        "show": {
                            "llmMemoryType": "windowSize"
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                        "id": "llmAgentflow_0-input-llmMemoryWindowSize-number",
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                        "label": "Max Token Limit",
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                        "show": {
                            "llmMemoryType": "conversationSummaryBuffer"
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                        "label": "Input Message",
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                        "type": "string",
                        "description": "Add an input message as user message at the end of the conversation",
                        "rows": 4,
                        "optional": true,
                        "acceptVariable": true,
                        "show": {
                            "llmEnableMemory": true
                        },
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                    {
                        "label": "Return Response As",
                        "name": "llmReturnResponseAs",
                        "type": "options",
                        "options": [
                            {
                                "label": "User Message",
                                "name": "userMessage"
                            },
                            {
                                "label": "Assistant Message",
                                "name": "assistantMessage"
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                        ],
                        "default": "userMessage",
                        "id": "llmAgentflow_0-input-llmReturnResponseAs-options",
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                    },
                    {
                        "label": "JSON Structured Output",
                        "name": "llmStructuredOutput",
                        "description": "Instruct the LLM to give output in a JSON structured schema",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
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                                "label": "Key",
                                "name": "key",
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                                "label": "Type",
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                                "options": [
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                                        "label": "String",
                                        "name": "string"
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                                        "label": "String Array",
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                                        "label": "Number",
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                                    {
                                        "label": "Boolean",
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                                    {
                                        "label": "Enum",
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                                    {
                                        "label": "JSON Array",
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                                ]
                            },
                            {
                                "label": "Enum Values",
                                "name": "enumValues",
                                "type": "string",
                                "placeholder": "value1, value2, value3",
                                "description": "Enum values. Separated by comma",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "enum"
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                            },
                            {
                                "label": "JSON Schema",
                                "name": "jsonSchema",
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                                "placeholder": "{\n    \"answer\": {\n        \"type\": \"string\",\n        \"description\": \"Value of the answer\"\n    },\n    \"reason\": {\n        \"type\": \"string\",\n        \"description\": \"Reason for the answer\"\n    },\n    \"optional\": {\n        \"type\": \"boolean\"\n    },\n    \"count\": {\n        \"type\": \"number\"\n    },\n    \"children\": {\n        \"type\": \"array\",\n        \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n                \"value\": {\n                    \"type\": \"string\",\n                    \"description\": \"Value of the children's answer\"\n                }\n            }\n        }\n    }\n}",
                                "description": "JSON schema for the structured output",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "jsonArray"
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                            },
                            {
                                "label": "Description",
                                "name": "description",
                                "type": "string",
                                "placeholder": "Description of the key"
                            }
                        ],
                        "id": "llmAgentflow_0-input-llmStructuredOutput-array",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "llmUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
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                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "llmAgentflow_0-input-llmUpdateState-array",
                        "display": true
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                ],
                "inputAnchors": [],
                "inputs": {
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                    "llmMessages": [
                        {
                            "role": "developer",
                            "content": "<p>Your only role is to improve the user query for more clarity. Do not add any meta comments.</p>"
                        }
                    ],
                    "llmEnableMemory": false,
                    "llmReturnResponseAs": "userMessage",
                    "llmStructuredOutput": "",
                    "llmUpdateState": "",
                    "llmModelConfig": {
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                        "modelName": "gpt-4o-mini",
                        "temperature": "0.5",
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                        "topP": "",
                        "frequencyPenalty": "",
                        "presencePenalty": "",
                        "timeout": "",
                        "strictToolCalling": "",
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                        "basepath": "",
                        "proxyUrl": "",
                        "baseOptions": "",
                        "allowImageUploads": "",
                        "imageResolution": "low",
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                        "llmModel": "chatOpenAI"
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                },
                "outputAnchors": [
                    {
                        "id": "llmAgentflow_0-output-llmAgentflow",
                        "label": "LLM",
                        "name": "llmAgentflow"
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                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
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            "height": 72,
            "selected": false,
            "positionAbsolute": {
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        {
            "id": "agentAgentflow_0",
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                "id": "agentAgentflow_0",
                "label": "Agent 0",
                "version": 1,
                "name": "agentAgentflow",
                "type": "Agent",
                "color": "#4DD0E1",
                "baseClasses": ["Agent"],
                "category": "Agent Flows",
                "description": "Dynamically choose and utilize tools during runtime, enabling multi-step reasoning",
                "inputParams": [
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                        "label": "Model",
                        "name": "agentModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "agentAgentflow_0-input-agentModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Messages",
                        "name": "agentMessages",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
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                                "label": "Role",
                                "name": "role",
                                "type": "options",
                                "options": [
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                                        "label": "System",
                                        "name": "system"
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                                        "label": "Assistant",
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                                        "label": "Developer",
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                                        "label": "User",
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                                "name": "content",
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                                "generateInstruction": true,
                                "rows": 4
                            }
                        ],
                        "id": "agentAgentflow_0-input-agentMessages-array",
                        "display": true
                    },
                    {
                        "label": "Tools",
                        "name": "agentTools",
                        "type": "array",
                        "optional": true,
                        "array": [
                            {
                                "label": "Tool",
                                "name": "agentSelectedTool",
                                "type": "asyncOptions",
                                "loadMethod": "listTools",
                                "loadConfig": true
                            },
                            {
                                "label": "Require Human Input",
                                "name": "agentSelectedToolRequiresHumanInput",
                                "type": "boolean",
                                "optional": true
                            }
                        ],
                        "id": "agentAgentflow_0-input-agentTools-array",
                        "display": true
                    },
                    {
                        "label": "Knowledge (Document Stores)",
                        "name": "agentKnowledgeDocumentStores",
                        "type": "array",
                        "description": "Give your agent context about different document sources. Document stores must be upserted in advance.",
                        "array": [
                            {
                                "label": "Document Store",
                                "name": "documentStore",
                                "type": "asyncOptions",
                                "loadMethod": "listStores"
                            },
                            {
                                "label": "Describe Knowledge",
                                "name": "docStoreDescription",
                                "type": "string",
                                "generateDocStoreDescription": true,
                                "placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
                                "rows": 4
                            },
                            {
                                "label": "Return Source Documents",
                                "name": "returnSourceDocuments",
                                "type": "boolean",
                                "optional": true
                            }
                        ],
                        "optional": true,
                        "id": "agentAgentflow_0-input-agentKnowledgeDocumentStores-array",
                        "display": true
                    },
                    {
                        "label": "Knowledge (Vector Embeddings)",
                        "name": "agentKnowledgeVSEmbeddings",
                        "type": "array",
                        "description": "Give your agent context about different document sources from existing vector stores and embeddings",
                        "array": [
                            {
                                "label": "Vector Store",
                                "name": "vectorStore",
                                "type": "asyncOptions",
                                "loadMethod": "listVectorStores",
                                "loadConfig": true
                            },
                            {
                                "label": "Embedding Model",
                                "name": "embeddingModel",
                                "type": "asyncOptions",
                                "loadMethod": "listEmbeddings",
                                "loadConfig": true
                            },
                            {
                                "label": "Knowledge Name",
                                "name": "knowledgeName",
                                "type": "string",
                                "placeholder": "A short name for the knowledge base, this is useful for the AI to know when and how to search for correct information"
                            },
                            {
                                "label": "Describe Knowledge",
                                "name": "knowledgeDescription",
                                "type": "string",
                                "placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
                                "rows": 4
                            },
                            {
                                "label": "Return Source Documents",
                                "name": "returnSourceDocuments",
                                "type": "boolean",
                                "optional": true
                            }
                        ],
                        "optional": true,
                        "id": "agentAgentflow_0-input-agentKnowledgeVSEmbeddings-array",
                        "display": true
                    },
                    {
                        "label": "Enable Memory",
                        "name": "agentEnableMemory",
                        "type": "boolean",
                        "description": "Enable memory for the conversation thread",
                        "default": true,
                        "optional": true,
                        "id": "agentAgentflow_0-input-agentEnableMemory-boolean",
                        "display": true
                    },
                    {
                        "label": "Memory Type",
                        "name": "agentMemoryType",
                        "type": "options",
                        "options": [
                            {
                                "label": "All Messages",
                                "name": "allMessages",
                                "description": "Retrieve all messages from the conversation"
                            },
                            {
                                "label": "Window Size",
                                "name": "windowSize",
                                "description": "Uses a fixed window size to surface the last N messages"
                            },
                            {
                                "label": "Conversation Summary",
                                "name": "conversationSummary",
                                "description": "Summarizes the whole conversation"
                            },
                            {
                                "label": "Conversation Summary Buffer",
                                "name": "conversationSummaryBuffer",
                                "description": "Summarize conversations once token limit is reached. Default to 2000"
                            }
                        ],
                        "optional": true,
                        "default": "allMessages",
                        "show": {
                            "agentEnableMemory": true
                        },
                        "id": "agentAgentflow_0-input-agentMemoryType-options",
                        "display": true
                    },
                    {
                        "label": "Window Size",
                        "name": "agentMemoryWindowSize",
                        "type": "number",
                        "default": "20",
                        "description": "Uses a fixed window size to surface the last N messages",
                        "show": {
                            "agentMemoryType": "windowSize"
                        },
                        "id": "agentAgentflow_0-input-agentMemoryWindowSize-number",
                        "display": false
                    },
                    {
                        "label": "Max Token Limit",
                        "name": "agentMemoryMaxTokenLimit",
                        "type": "number",
                        "default": "2000",
                        "description": "Summarize conversations once token limit is reached. Default to 2000",
                        "show": {
                            "agentMemoryType": "conversationSummaryBuffer"
                        },
                        "id": "agentAgentflow_0-input-agentMemoryMaxTokenLimit-number",
                        "display": false
                    },
                    {
                        "label": "Input Message",
                        "name": "agentUserMessage",
                        "type": "string",
                        "description": "Add an input message as user message at the end of the conversation",
                        "rows": 4,
                        "optional": true,
                        "acceptVariable": true,
                        "show": {
                            "agentEnableMemory": true
                        },
                        "id": "agentAgentflow_0-input-agentUserMessage-string",
                        "display": true
                    },
                    {
                        "label": "Return Response As",
                        "name": "agentReturnResponseAs",
                        "type": "options",
                        "options": [
                            {
                                "label": "User Message",
                                "name": "userMessage"
                            },
                            {
                                "label": "Assistant Message",
                                "name": "assistantMessage"
                            }
                        ],
                        "default": "userMessage",
                        "id": "agentAgentflow_0-input-agentReturnResponseAs-options",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "agentUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
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                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "agentAgentflow_0-input-agentUpdateState-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "agentModel": "chatGoogleGenerativeAI",
                    "agentMessages": [
                        {
                            "role": "system",
                            "content": "<p>You are Agent 0. Your goal is to explore any topic provided by the user in depth with Agent 1.</p><ol><li><p>Start: Introduce the topic to Agent 1. Share your initial thoughts and any assumptions you have.</p></li><li><p>Research &amp; Share:</p><ul><li><p>Use <strong>BraveSearch API</strong> to find a range of information and different viewpoints on the topic. Look for URLs that seem promising for more detail.</p></li><li><p>If a URL from BraveSearch API (or one you already know) seems particularly important, use the <strong>Web Scraper Tool</strong> to get its full content.</p></li><li><p>Present what you find to Agent 1, especially any complexities, counter-arguments, or conflicting data.</p></li><li><p>Clearly state your sources:</p><ul><li><p>\"BraveSearch API found...\"</p></li><li><p>\"After scraping [URL], the content shows...\"</p></li></ul></li></ul></li><li><p>Discuss &amp; Deepen:</p><ul><li><p>Listen to Agent 1. Ask probing questions.</p></li><li><p>If needed, use your tools again (BraveSearch API to find more, Web Scraper to analyze a specific page) during the conversation to verify points or explore new angles.</p></li></ul></li><li><p>Mindset: Be curious, analytical, and open to different perspectives. Aim for a thorough understanding, not just agreement.</p></li></ol>"
                        }
                    ],
                    "agentTools": [
                        {
                            "agentSelectedTool": "webScraperTool",
                            "agentSelectedToolRequiresHumanInput": "",
                            "agentSelectedToolConfig": {
                                "scrapeMode": "recursive",
                                "maxDepth": 1,
                                "maxPages": 10,
                                "timeoutS": 60,
                                "description": "",
                                "agentSelectedTool": "webScraperTool"
                            }
                        },
                        {
                            "agentSelectedTool": "braveSearchAPI",
                            "agentSelectedToolRequiresHumanInput": "",
                            "agentSelectedToolConfig": {
                                "agentSelectedTool": "braveSearchAPI"
                            }
                        }
                    ],
                    "agentKnowledgeDocumentStores": "",
                    "agentKnowledgeVSEmbeddings": "",
                    "agentEnableMemory": true,
                    "agentMemoryType": "allMessages",
                    "agentUserMessage": "",
                    "agentReturnResponseAs": "assistantMessage",
                    "agentUpdateState": "",
                    "agentModelConfig": {
                        "cache": "",
                        "contextCache": "",
                        "modelName": "gemini-2.0-flash",
                        "customModelName": "",
                        "temperature": "0.5",
                        "streaming": true,
                        "maxOutputTokens": "",
                        "topP": "",
                        "topK": "",
                        "harmCategory": "",
                        "harmBlockThreshold": "",
                        "baseUrl": "",
                        "allowImageUploads": "",
                        "agentModel": "chatGoogleGenerativeAI"
                    }
                },
                "outputAnchors": [
                    {
                        "id": "agentAgentflow_0-output-agentAgentflow",
                        "label": "Agent",
                        "name": "agentAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 200,
            "height": 100,
            "selected": false,
            "positionAbsolute": {
                "x": -26.136703307904796,
                "y": 72.89650466398558
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            "dragging": false
        },
        {
            "id": "agentAgentflow_1",
            "position": {
                "x": 210.25517525319754,
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            "data": {
                "id": "agentAgentflow_1",
                "label": "Agent 1",
                "version": 1,
                "name": "agentAgentflow",
                "type": "Agent",
                "color": "#4DD0E1",
                "baseClasses": ["Agent"],
                "category": "Agent Flows",
                "description": "Dynamically choose and utilize tools during runtime, enabling multi-step reasoning",
                "inputParams": [
                    {
                        "label": "Model",
                        "name": "agentModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "agentAgentflow_1-input-agentModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Messages",
                        "name": "agentMessages",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Role",
                                "name": "role",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "System",
                                        "name": "system"
                                    },
                                    {
                                        "label": "Assistant",
                                        "name": "assistant"
                                    },
                                    {
                                        "label": "Developer",
                                        "name": "developer"
                                    },
                                    {
                                        "label": "User",
                                        "name": "user"
                                    }
                                ]
                            },
                            {
                                "label": "Content",
                                "name": "content",
                                "type": "string",
                                "acceptVariable": true,
                                "generateInstruction": true,
                                "rows": 4
                            }
                        ],
                        "id": "agentAgentflow_1-input-agentMessages-array",
                        "display": true
                    },
                    {
                        "label": "Tools",
                        "name": "agentTools",
                        "type": "array",
                        "optional": true,
                        "array": [
                            {
                                "label": "Tool",
                                "name": "agentSelectedTool",
                                "type": "asyncOptions",
                                "loadMethod": "listTools",
                                "loadConfig": true
                            },
                            {
                                "label": "Require Human Input",
                                "name": "agentSelectedToolRequiresHumanInput",
                                "type": "boolean",
                                "optional": true
                            }
                        ],
                        "id": "agentAgentflow_1-input-agentTools-array",
                        "display": true
                    },
                    {
                        "label": "Knowledge (Document Stores)",
                        "name": "agentKnowledgeDocumentStores",
                        "type": "array",
                        "description": "Give your agent context about different document sources. Document stores must be upserted in advance.",
                        "array": [
                            {
                                "label": "Document Store",
                                "name": "documentStore",
                                "type": "asyncOptions",
                                "loadMethod": "listStores"
                            },
                            {
                                "label": "Describe Knowledge",
                                "name": "docStoreDescription",
                                "type": "string",
                                "generateDocStoreDescription": true,
                                "placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
                                "rows": 4
                            },
                            {
                                "label": "Return Source Documents",
                                "name": "returnSourceDocuments",
                                "type": "boolean",
                                "optional": true
                            }
                        ],
                        "optional": true,
                        "id": "agentAgentflow_1-input-agentKnowledgeDocumentStores-array",
                        "display": true
                    },
                    {
                        "label": "Knowledge (Vector Embeddings)",
                        "name": "agentKnowledgeVSEmbeddings",
                        "type": "array",
                        "description": "Give your agent context about different document sources from existing vector stores and embeddings",
                        "array": [
                            {
                                "label": "Vector Store",
                                "name": "vectorStore",
                                "type": "asyncOptions",
                                "loadMethod": "listVectorStores",
                                "loadConfig": true
                            },
                            {
                                "label": "Embedding Model",
                                "name": "embeddingModel",
                                "type": "asyncOptions",
                                "loadMethod": "listEmbeddings",
                                "loadConfig": true
                            },
                            {
                                "label": "Knowledge Name",
                                "name": "knowledgeName",
                                "type": "string",
                                "placeholder": "A short name for the knowledge base, this is useful for the AI to know when and how to search for correct information"
                            },
                            {
                                "label": "Describe Knowledge",
                                "name": "knowledgeDescription",
                                "type": "string",
                                "placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
                                "rows": 4
                            },
                            {
                                "label": "Return Source Documents",
                                "name": "returnSourceDocuments",
                                "type": "boolean",
                                "optional": true
                            }
                        ],
                        "optional": true,
                        "id": "agentAgentflow_1-input-agentKnowledgeVSEmbeddings-array",
                        "display": true
                    },
                    {
                        "label": "Enable Memory",
                        "name": "agentEnableMemory",
                        "type": "boolean",
                        "description": "Enable memory for the conversation thread",
                        "default": true,
                        "optional": true,
                        "id": "agentAgentflow_1-input-agentEnableMemory-boolean",
                        "display": true
                    },
                    {
                        "label": "Memory Type",
                        "name": "agentMemoryType",
                        "type": "options",
                        "options": [
                            {
                                "label": "All Messages",
                                "name": "allMessages",
                                "description": "Retrieve all messages from the conversation"
                            },
                            {
                                "label": "Window Size",
                                "name": "windowSize",
                                "description": "Uses a fixed window size to surface the last N messages"
                            },
                            {
                                "label": "Conversation Summary",
                                "name": "conversationSummary",
                                "description": "Summarizes the whole conversation"
                            },
                            {
                                "label": "Conversation Summary Buffer",
                                "name": "conversationSummaryBuffer",
                                "description": "Summarize conversations once token limit is reached. Default to 2000"
                            }
                        ],
                        "optional": true,
                        "default": "allMessages",
                        "show": {
                            "agentEnableMemory": true
                        },
                        "id": "agentAgentflow_1-input-agentMemoryType-options",
                        "display": true
                    },
                    {
                        "label": "Window Size",
                        "name": "agentMemoryWindowSize",
                        "type": "number",
                        "default": "20",
                        "description": "Uses a fixed window size to surface the last N messages",
                        "show": {
                            "agentMemoryType": "windowSize"
                        },
                        "id": "agentAgentflow_1-input-agentMemoryWindowSize-number",
                        "display": false
                    },
                    {
                        "label": "Max Token Limit",
                        "name": "agentMemoryMaxTokenLimit",
                        "type": "number",
                        "default": "2000",
                        "description": "Summarize conversations once token limit is reached. Default to 2000",
                        "show": {
                            "agentMemoryType": "conversationSummaryBuffer"
                        },
                        "id": "agentAgentflow_1-input-agentMemoryMaxTokenLimit-number",
                        "display": false
                    },
                    {
                        "label": "Input Message",
                        "name": "agentUserMessage",
                        "type": "string",
                        "description": "Add an input message as user message at the end of the conversation",
                        "rows": 4,
                        "optional": true,
                        "acceptVariable": true,
                        "show": {
                            "agentEnableMemory": true
                        },
                        "id": "agentAgentflow_1-input-agentUserMessage-string",
                        "display": true
                    },
                    {
                        "label": "Return Response As",
                        "name": "agentReturnResponseAs",
                        "type": "options",
                        "options": [
                            {
                                "label": "User Message",
                                "name": "userMessage"
                            },
                            {
                                "label": "Assistant Message",
                                "name": "assistantMessage"
                            }
                        ],
                        "default": "userMessage",
                        "id": "agentAgentflow_1-input-agentReturnResponseAs-options",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "agentUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "agentAgentflow_1-input-agentUpdateState-array",
                        "display": true
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                ],
                "inputAnchors": [],
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                            "role": "system",
                            "content": "<p>You are Agent 1. Your goal is to explore a topic in depth with Agent 0.</p><ol><li><p>Respond &amp; Share:</p><ul><li><p>Acknowledge the topic Agent 0 introduces.</p></li><li><p>Share your own thoughts and feelings, building on or respectfully challenging Agent 0's points. Consider your own assumptions.</p></li></ul></li><li><p>Research &amp; Contribute:</p><ul><li><p>Use <strong>BraveSearch API</strong> to research the topic, especially looking for different perspectives, counter-arguments, or aspects Agent 0 might not have covered. Identify URLs that seem promising for more detail.</p></li><li><p>If a URL from BraveSearch API (or one you already know) seems particularly important for your point or for adding nuance, use the <strong>Web Scraper Tool</strong> to get its full content.</p></li><li><p>Present your findings, especially any that introduce new angles, conflicts, or alternative views.</p></li><li><p>Clearly state your sources:</p><ul><li><p>\"My BraveSearch API tool found...\"</p></li><li><p>\"After scraping [URL], the content suggests...\"</p></li></ul></li><li><p>If you find conflicting info from different sources, point this out.</p></li></ul></li><li><p>Discuss &amp; Deepen:</p><ul><li><p>Listen carefully to Agent 0. Ask clarifying questions and questions that challenge their reasoning or explore alternatives.</p></li><li><p>If needed, use your tools again (BraveSearch API to find more, Web Scraper to analyze a specific page) during the conversation to support your points or investigate Agent 0's claims.</p></li></ul></li><li><p>Mindset: Be respectful, analytical, and open to different viewpoints. Aim for a thorough exploration and constructive disagreement, backed by research.</p></li></ol>"
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                    ],
                    "agentTools": [
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                            "agentSelectedTool": "webScraperTool",
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                            "agentSelectedToolConfig": {
                                "scrapeMode": "recursive",
                                "maxDepth": 1,
                                "maxPages": 10,
                                "timeoutS": 60,
                                "description": "",
                                "agentSelectedTool": "webScraperTool"
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                        },
                        {
                            "agentSelectedTool": "braveSearchAPI",
                            "agentSelectedToolRequiresHumanInput": "",
                            "agentSelectedToolConfig": {
                                "agentSelectedTool": "braveSearchAPI"
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                    "agentKnowledgeDocumentStores": "",
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                    "agentReturnResponseAs": "assistantMessage",
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                        "contextCache": "",
                        "modelName": "gemini-2.0-flash",
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                        "harmCategory": "",
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                        "baseUrl": "",
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                        "agentModel": "chatGoogleGenerativeAI"
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                "outputAnchors": [
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                        "id": "agentAgentflow_1-output-agentAgentflow",
                        "label": "Agent",
                        "name": "agentAgentflow"
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            "id": "conditionAgentflow_0",
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                "id": "conditionAgentflow_0",
                "label": "Check Iterations",
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                "name": "conditionAgentflow",
                "type": "Condition",
                "color": "#FFB938",
                "baseClasses": ["Condition"],
                "category": "Agent Flows",
                "description": "Split flows based on If Else conditions",
                "inputParams": [
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                        "label": "Conditions",
                        "name": "conditions",
                        "type": "array",
                        "description": "Values to compare",
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                                "type": "number",
                                "value1": "",
                                "operation": "equal",
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                                "label": "Type",
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                                "options": [
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                                        "label": "String",
                                        "name": "string"
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                                    {
                                        "label": "Number",
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                                    {
                                        "label": "Boolean",
                                        "name": "boolean"
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                            {
                                "label": "Value 1",
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                            {
                                "label": "Operation",
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                                    {
                                        "label": "Contains",
                                        "name": "contains"
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                                    {
                                        "label": "Ends With",
                                        "name": "endsWith"
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                                        "label": "Equal",
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                                        "label": "Not Contains",
                                        "name": "notContains"
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                                    {
                                        "label": "Not Equal",
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                                    {
                                        "label": "Regex",
                                        "name": "regex"
                                    },
                                    {
                                        "label": "Starts With",
                                        "name": "startsWith"
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                                    {
                                        "label": "Is Empty",
                                        "name": "isEmpty"
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                                    {
                                        "label": "Not Empty",
                                        "name": "notEmpty"
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                                "default": "equal",
                                "description": "Type of operation",
                                "show": {
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                            },
                            {
                                "label": "Value 2",
                                "name": "value2",
                                "type": "string",
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                                "description": "Second value to be compared with",
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                                "show": {
                                    "conditions[$index].type": "string"
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                                "hide": {
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                            {
                                "label": "Value 1",
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                                "description": "First value to be compared with",
                                "acceptVariable": true,
                                "show": {
                                    "conditions[$index].type": "number"
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                            {
                                "label": "Operation",
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                                "options": [
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                                        "label": "Smaller",
                                        "name": "smaller"
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                                        "label": "Equal",
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                                        "label": "Not Equal",
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                                        "label": "Larger",
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                                        "label": "Larger Equal",
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                                "default": "equal",
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                                "default": "equal",
                                "description": "Type of operation",
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                            {
                                "label": "Value 2",
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                ],
                "inputAnchors": [],
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                            "type": "number",
                            "value1": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"runtime_messages_length\" data-label=\"runtime_messages_length\">{{ runtime_messages_length }}</span> </p>",
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                            "value2": "<p>11</p>"
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                    ]
                },
                "outputAnchors": [
                    {
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                    {
                        "id": "conditionAgentflow_0-output-1",
                        "label": "Condition",
                        "name": "conditionAgentflow"
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                "outputs": {
                    "conditionAgentflow": ""
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            "data": {
                "id": "loopAgentflow_0",
                "label": "Loop Back to Agent 0",
                "version": 1,
                "name": "loopAgentflow",
                "type": "Loop",
                "color": "#FFA07A",
                "hideOutput": true,
                "baseClasses": ["Loop"],
                "category": "Agent Flows",
                "description": "Loop back to a previous node",
                "inputParams": [
                    {
                        "label": "Loop Back To",
                        "name": "loopBackToNode",
                        "type": "asyncOptions",
                        "loadMethod": "listPreviousNodes",
                        "freeSolo": true,
                        "id": "loopAgentflow_0-input-loopBackToNode-asyncOptions",
                        "display": true
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                    {
                        "label": "Max Loop Count",
                        "name": "maxLoopCount",
                        "type": "number",
                        "default": 5,
                        "id": "loopAgentflow_0-input-maxLoopCount-number",
                        "display": true
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                ],
                "inputAnchors": [],
                "inputs": {
                    "loopBackToNode": "agentAgentflow_0-Agent 0",
                    "maxLoopCount": "10"
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                "outputAnchors": [],
                "outputs": {},
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        {
            "id": "llmAgentflow_1",
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            "data": {
                "id": "llmAgentflow_1",
                "label": "Agent 2",
                "version": 1,
                "name": "llmAgentflow",
                "type": "LLM",
                "color": "#64B5F6",
                "baseClasses": ["LLM"],
                "category": "Agent Flows",
                "description": "Large language models to analyze user-provided inputs and generate responses",
                "inputParams": [
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                        "label": "Model",
                        "name": "llmModel",
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                        "loadMethod": "listModels",
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                        "id": "llmAgentflow_1-input-llmModel-asyncOptions",
                        "display": true
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                    {
                        "label": "Messages",
                        "name": "llmMessages",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
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                                "label": "Role",
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                                "options": [
                                    {
                                        "label": "System",
                                        "name": "system"
                                    },
                                    {
                                        "label": "Assistant",
                                        "name": "assistant"
                                    },
                                    {
                                        "label": "Developer",
                                        "name": "developer"
                                    },
                                    {
                                        "label": "User",
                                        "name": "user"
                                    }
                                ]
                            },
                            {
                                "label": "Content",
                                "name": "content",
                                "type": "string",
                                "acceptVariable": true,
                                "generateInstruction": true,
                                "rows": 4
                            }
                        ],
                        "id": "llmAgentflow_1-input-llmMessages-array",
                        "display": true
                    },
                    {
                        "label": "Enable Memory",
                        "name": "llmEnableMemory",
                        "type": "boolean",
                        "description": "Enable memory for the conversation thread",
                        "default": true,
                        "optional": true,
                        "id": "llmAgentflow_1-input-llmEnableMemory-boolean",
                        "display": true
                    },
                    {
                        "label": "Memory Type",
                        "name": "llmMemoryType",
                        "type": "options",
                        "options": [
                            {
                                "label": "All Messages",
                                "name": "allMessages",
                                "description": "Retrieve all messages from the conversation"
                            },
                            {
                                "label": "Window Size",
                                "name": "windowSize",
                                "description": "Uses a fixed window size to surface the last N messages"
                            },
                            {
                                "label": "Conversation Summary",
                                "name": "conversationSummary",
                                "description": "Summarizes the whole conversation"
                            },
                            {
                                "label": "Conversation Summary Buffer",
                                "name": "conversationSummaryBuffer",
                                "description": "Summarize conversations once token limit is reached. Default to 2000"
                            }
                        ],
                        "optional": true,
                        "default": "allMessages",
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_1-input-llmMemoryType-options",
                        "display": false
                    },
                    {
                        "label": "Window Size",
                        "name": "llmMemoryWindowSize",
                        "type": "number",
                        "default": "20",
                        "description": "Uses a fixed window size to surface the last N messages",
                        "show": {
                            "llmMemoryType": "windowSize"
                        },
                        "id": "llmAgentflow_1-input-llmMemoryWindowSize-number",
                        "display": false
                    },
                    {
                        "label": "Max Token Limit",
                        "name": "llmMemoryMaxTokenLimit",
                        "type": "number",
                        "default": "2000",
                        "description": "Summarize conversations once token limit is reached. Default to 2000",
                        "show": {
                            "llmMemoryType": "conversationSummaryBuffer"
                        },
                        "id": "llmAgentflow_1-input-llmMemoryMaxTokenLimit-number",
                        "display": false
                    },
                    {
                        "label": "Input Message",
                        "name": "llmUserMessage",
                        "type": "string",
                        "description": "Add an input message as user message at the end of the conversation",
                        "rows": 4,
                        "optional": true,
                        "acceptVariable": true,
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_1-input-llmUserMessage-string",
                        "display": false
                    },
                    {
                        "label": "Return Response As",
                        "name": "llmReturnResponseAs",
                        "type": "options",
                        "options": [
                            {
                                "label": "User Message",
                                "name": "userMessage"
                            },
                            {
                                "label": "Assistant Message",
                                "name": "assistantMessage"
                            }
                        ],
                        "default": "userMessage",
                        "id": "llmAgentflow_1-input-llmReturnResponseAs-options",
                        "display": true
                    },
                    {
                        "label": "JSON Structured Output",
                        "name": "llmStructuredOutput",
                        "description": "Instruct the LLM to give output in a JSON structured schema",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "string"
                            },
                            {
                                "label": "Type",
                                "name": "type",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "String",
                                        "name": "string"
                                    },
                                    {
                                        "label": "String Array",
                                        "name": "stringArray"
                                    },
                                    {
                                        "label": "Number",
                                        "name": "number"
                                    },
                                    {
                                        "label": "Boolean",
                                        "name": "boolean"
                                    },
                                    {
                                        "label": "Enum",
                                        "name": "enum"
                                    },
                                    {
                                        "label": "JSON Array",
                                        "name": "jsonArray"
                                    }
                                ]
                            },
                            {
                                "label": "Enum Values",
                                "name": "enumValues",
                                "type": "string",
                                "placeholder": "value1, value2, value3",
                                "description": "Enum values. Separated by comma",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "enum"
                                }
                            },
                            {
                                "label": "JSON Schema",
                                "name": "jsonSchema",
                                "type": "code",
                                "placeholder": "{\n    \"answer\": {\n        \"type\": \"string\",\n        \"description\": \"Value of the answer\"\n    },\n    \"reason\": {\n        \"type\": \"string\",\n        \"description\": \"Reason for the answer\"\n    },\n    \"optional\": {\n        \"type\": \"boolean\"\n    },\n    \"count\": {\n        \"type\": \"number\"\n    },\n    \"children\": {\n        \"type\": \"array\",\n        \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n                \"value\": {\n                    \"type\": \"string\",\n                    \"description\": \"Value of the children's answer\"\n                }\n            }\n        }\n    }\n}",
                                "description": "JSON schema for the structured output",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "jsonArray"
                                }
                            },
                            {
                                "label": "Description",
                                "name": "description",
                                "type": "string",
                                "placeholder": "Description of the key"
                            }
                        ],
                        "id": "llmAgentflow_1-input-llmStructuredOutput-array",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "llmUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "llmAgentflow_1-input-llmUpdateState-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "llmModel": "chatGoogleGenerativeAI",
                    "llmMessages": [
                        {
                            "role": "system",
                            "content": "<p>You are Agent 2. Your role is to transform the deep conversation between Agent 0 and Agent 1 into a comprehensive and extensive white paper on the subject they discussed.</p><p>Your goal is to produce an authoritative document that not only captures the essence of their dialogue but also expands upon it, providing a thorough exploration of the topic. This white paper should be suitable for an audience seeking a deep understanding of the subject.</p><p>The white paper must include, but is not limited to, the following sections and considerations:</p><ol><li><p>Title: A clear, compelling title for the white paper that reflects the core subject.</p></li><li><p>Abstract/Executive Summary: A concise overview (approx. 200-300 words) of the white paper's main arguments, scope, and conclusions, derived from the conversation.</p></li><li><p>Introduction:</p><ul><li><p>Set the context and importance of the subject discussed by Agent 0 and Agent 1.</p></li><li><p>Clearly define the central problem, question, or theme that the white paper will address, based on their dialogue.</p></li><li><p>Outline the paper's structure and objectives.</p></li></ul></li><li><p>Main Body / Thematic Analysis (Multiple Sections):</p><ul><li><p>Deconstruct and Synthesize Key Arguments: Detail the principal arguments, propositions, and evidence presented by both Agent 0 and Agent 1. Go beyond mere listing; analyze the strengths, weaknesses, and underlying assumptions of their positions.</p></li><li><p>Explore Core Themes and Concepts: Identify and elaborate on the major themes and concepts that emerged. For each theme, discuss how Agent 0 and Agent 1 approached it, their points of convergence, and their points of divergence.</p></li><li><p>Analyze the Evolution of the Discussion: Trace how the understanding of the subject evolved throughout their conversation. Highlight any shifts in perspective, critical turning points, challenged assumptions, or moments of significant clarification.</p></li><li><p>Evidence and Examples: Where the agents provided examples or evidence, incorporate and potentially expand upon these to support the white paper's analysis.</p></li></ul></li><li><p>Synthesis of Insights and Key Conclusions:</p><ul><li><p>Draw together the most significant insights and conclusions that can be derived from the entirety of the conversation.</p></li><li><p>This section should offer a consolidated understanding of the subject, informed by the agents' interaction.</p></li></ul></li><li><p>Implications and Future Directions:</p><ul><li><p>Discuss the broader implications of the insights and conclusions reached.</p></li><li><p>Identify any unresolved questions, ambiguities, or areas that the conversation indicated require further exploration or research.</p></li><li><p>Suggest potential next steps or future avenues of inquiry.</p></li></ul></li><li><p>Conclusion: A strong concluding section summarizing the white paper's main findings, their significance, and a final thought on the subject.</p></li></ol><p>Style and Tone:</p><ul><li><p>Extensive and In-depth: The paper should be thorough and detailed.</p></li><li><p>Well-Structured: Use clear headings, subheadings, and logical flow.</p></li><li><p>Analytical and Critical: Do not just report; analyze, interpret, and critically engage with the agents' ideas.</p></li><li><p>Objective and Authoritative: While based on the agents' dialogue, the white paper should present a balanced and well-reasoned perspective.</p></li><li><p>Clear Attribution: When discussing specific viewpoints or arguments, clearly attribute them to Agent 0 or Agent 1.</p></li><li><p>Formal and Professional Language: Maintain a tone appropriate for a white paper.</p></li></ul><p>Your primary source material is the conversation between Agent 0 and Agent 1. Your task is to elevate their discourse into a structured, analytical, and extensive white paper.</p>"
                        },
                        {
                            "role": "user",
                            "content": "<p>Here is the full conversation between Agent 0 and Agent 1. Please use this as the primary source material for generating the extensive white paper as per your instructions:<br>--<br><span class=\"variable\" data-type=\"mention\" data-id=\"chat_history\" data-label=\"chat_history\">{{ chat_history }}</span> <br>--</p>"
                        }
                    ],
                    "llmEnableMemory": false,
                    "llmReturnResponseAs": "assistantMessage",
                    "llmStructuredOutput": "",
                    "llmUpdateState": "",
                    "llmModelConfig": {
                        "cache": "",
                        "contextCache": "",
                        "modelName": "gemini-2.0-flash",
                        "customModelName": "",
                        "temperature": "0.5",
                        "streaming": true,
                        "maxOutputTokens": "",
                        "topP": "",
                        "topK": "",
                        "harmCategory": "",
                        "harmBlockThreshold": "",
                        "baseUrl": "",
                        "allowImageUploads": "",
                        "llmModel": "chatGoogleGenerativeAI"
                    }
                },
                "outputAnchors": [
                    {
                        "id": "llmAgentflow_1-output-llmAgentflow",
                        "label": "LLM",
                        "name": "llmAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 200,
            "height": 72,
            "selected": false,
            "positionAbsolute": {
                "x": 693.0529196789191,
                "y": 133.0683091126315
            },
            "dragging": false
        },
        {
            "id": "stickyNoteAgentflow_0",
            "position": {
                "x": -445.43094068657194,
                "y": -61.80279682682627
            },
            "data": {
                "id": "stickyNoteAgentflow_0",
                "label": "Sticky Note",
                "version": 1,
                "name": "stickyNoteAgentflow",
                "type": "StickyNote",
                "color": "#fee440",
                "baseClasses": ["StickyNote"],
                "category": "Agent Flows",
                "description": "Add notes to the agent flow",
                "inputParams": [
                    {
                        "label": "",
                        "name": "note",
                        "type": "string",
                        "rows": 1,
                        "placeholder": "Type something here",
                        "optional": true,
                        "id": "stickyNoteAgentflow_0-input-note-string",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "note": "User provides a topic for research, for example: \"Humans in the Era of an ASI\""
                },
                "outputAnchors": [
                    {
                        "id": "stickyNoteAgentflow_0-output-stickyNoteAgentflow",
                        "label": "Sticky Note",
                        "name": "stickyNoteAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "stickyNote",
            "width": 210,
            "height": 123,
            "selected": false,
            "positionAbsolute": {
                "x": -445.43094068657194,
                "y": -61.80279682682627
            },
            "dragging": false
        },
        {
            "id": "stickyNoteAgentflow_1",
            "position": {
                "x": 454.90056136362915,
                "y": -146.44126039994615
            },
            "data": {
                "id": "stickyNoteAgentflow_1",
                "label": "Sticky Note (1)",
                "version": 1,
                "name": "stickyNoteAgentflow",
                "type": "StickyNote",
                "color": "#fee440",
                "baseClasses": ["StickyNote"],
                "category": "Agent Flows",
                "description": "Add notes to the agent flow",
                "inputParams": [
                    {
                        "label": "",
                        "name": "note",
                        "type": "string",
                        "rows": 1,
                        "placeholder": "Type something here",
                        "optional": true,
                        "id": "stickyNoteAgentflow_1-input-note-string",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "note": "Determine the number of back-and-forth exchanges between Agent 0 and Agent 1 in a deep conversation about the user's topic.  It is currently set for 5 iterations."
                },
                "outputAnchors": [
                    {
                        "id": "stickyNoteAgentflow_1-output-stickyNoteAgentflow",
                        "label": "Sticky Note",
                        "name": "stickyNoteAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "stickyNote",
            "width": 210,
            "height": 203,
            "selected": false,
            "positionAbsolute": {
                "x": 454.90056136362915,
                "y": -146.44126039994615
            },
            "dragging": false
        },
        {
            "id": "stickyNoteAgentflow_2",
            "position": {
                "x": 693.7511120802441,
                "y": 221.75098356027857
            },
            "data": {
                "id": "stickyNoteAgentflow_2",
                "label": "Sticky Note (1) (2)",
                "version": 1,
                "name": "stickyNoteAgentflow",
                "type": "StickyNote",
                "color": "#fee440",
                "baseClasses": ["StickyNote"],
                "category": "Agent Flows",
                "description": "Add notes to the agent flow",
                "inputParams": [
                    {
                        "label": "",
                        "name": "note",
                        "type": "string",
                        "rows": 1,
                        "placeholder": "Type something here",
                        "optional": true,
                        "id": "stickyNoteAgentflow_2-input-note-string",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "note": "This LLM Node transforms the in-depth conversation between Agent 0 and Agent 1 into a comprehensive white paper. It can be replaced with an Agent Node if you need to use tools such as sending the findings to our email, etc."
                },
                "outputAnchors": [
                    {
                        "id": "stickyNoteAgentflow_2-output-stickyNoteAgentflow",
                        "label": "Sticky Note",
                        "name": "stickyNoteAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "stickyNote",
            "width": 210,
            "height": 263,
            "selected": false,
            "positionAbsolute": {
                "x": 693.7511120802441,
                "y": 221.75098356027857
            },
            "dragging": false
        }
    ],
    "edges": [
        {
            "source": "startAgentflow_0",
            "sourceHandle": "startAgentflow_0-output-startAgentflow",
            "target": "llmAgentflow_0",
            "targetHandle": "llmAgentflow_0",
            "data": {
                "sourceColor": "#7EE787",
                "targetColor": "#64B5F6",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "startAgentflow_0-startAgentflow_0-output-startAgentflow-llmAgentflow_0-llmAgentflow_0"
        },
        {
            "source": "llmAgentflow_0",
            "sourceHandle": "llmAgentflow_0-output-llmAgentflow",
            "target": "agentAgentflow_0",
            "targetHandle": "agentAgentflow_0",
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            "type": "agentFlow",
            "id": "llmAgentflow_0-llmAgentflow_0-output-llmAgentflow-agentAgentflow_0-agentAgentflow_0"
        },
        {
            "source": "agentAgentflow_0",
            "sourceHandle": "agentAgentflow_0-output-agentAgentflow",
            "target": "agentAgentflow_1",
            "targetHandle": "agentAgentflow_1",
            "data": {
                "sourceColor": "#4DD0E1",
                "targetColor": "#4DD0E1",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "agentAgentflow_0-agentAgentflow_0-output-agentAgentflow-agentAgentflow_1-agentAgentflow_1"
        },
        {
            "source": "agentAgentflow_1",
            "sourceHandle": "agentAgentflow_1-output-agentAgentflow",
            "target": "conditionAgentflow_0",
            "targetHandle": "conditionAgentflow_0",
            "data": {
                "sourceColor": "#4DD0E1",
                "targetColor": "#FFB938",
                "isHumanInput": false
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            "type": "agentFlow",
            "id": "agentAgentflow_1-agentAgentflow_1-output-agentAgentflow-conditionAgentflow_0-conditionAgentflow_0"
        },
        {
            "source": "conditionAgentflow_0",
            "sourceHandle": "conditionAgentflow_0-output-0",
            "target": "loopAgentflow_0",
            "targetHandle": "loopAgentflow_0",
            "data": {
                "sourceColor": "#FFB938",
                "targetColor": "#FFA07A",
                "edgeLabel": "0",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "conditionAgentflow_0-conditionAgentflow_0-output-0-loopAgentflow_0-loopAgentflow_0"
        },
        {
            "source": "conditionAgentflow_0",
            "sourceHandle": "conditionAgentflow_0-output-1",
            "target": "llmAgentflow_1",
            "targetHandle": "llmAgentflow_1",
            "data": {
                "sourceColor": "#FFB938",
                "targetColor": "#64B5F6",
                "edgeLabel": "1",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "conditionAgentflow_0-conditionAgentflow_0-output-1-llmAgentflow_1-llmAgentflow_1"
        }
    ]
}
